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文章题目 LMI-Based Stability Criterion for Impulsive CGNNs via Fixed Point Theory 作者 Xiongrui Wang, Ruofeng Rao, Shouming Zhong 期刊 Mathematical Problems in Engineering 年 2015 期卷 页码 Volume 2015, Article ID 281681, 10 pages 全文链接 https://dx.doi.org/10.1155/2015/281681 |
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sunshan4379
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zh09: 金币+10 2016-12-25 22:30:03
lazy锦溪: LS-EPI+1 2016-12-26 09:45:51
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LMI-Based Stability Criterion for Impulsive CGNNs via Fixed Point Theory 作者:Wang, XR (Wang, Xiongrui)[ 1,2 ] ; Rao, RF (Rao, Ruofeng)[ 2 ] ; Zhong, SM (Zhong, Shouming)[ 3 ] MATHEMATICAL PROBLEMS IN ENGINEERING 文献号: 281681 DOI: 10.1155/2015/281681 出版年: 2015 查看期刊信息 摘要 Linear matrices inequalities (LMIs) method and the contraction mapping theorem were employed to prove the existence of globally exponentially stable trivial solution for impulsive Cohen-Grossberg neural networks (CGNNs). It is worth mentioning that it is the first time to use the contraction mapping theorem to prove the stability for CGNNs while only the Leray-Schauder fixed point theorem was applied in previous related literature. An example is given to illustrate the effectiveness of the proposed methods due to the large allowable variation range of impulse. 关键词 KeyWords Plus:GROSSBERG NEURAL-NETWORKS; TIME-VARYING DELAYS; EXPONENTIAL STABILITY; DIFFERENTIAL-EQUATIONS 作者信息 通讯作者地址: Rao, RF (通讯作者) Chengdu Normal Univ, Dept Math, Chengdu 611130, Peoples R China. 地址: [ 1 ] Yibin Univ, Dept Math, Yibin 644007, Peoples R China [ 2 ] Chengdu Normal Univ, Dept Math, Chengdu 611130, Peoples R China 显示增强组织信息的名称 [ 3 ] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 610054, Peoples R China 电子邮件地址:ruofengrao@163.com 基金资助致谢 基金资助机构 授权号 Scientific Research Fund of Science Technology Department of Sichuan Province 2012JY010 Sichuan Educational Committee Science Foundation 08ZB002 12ZB349 14ZA0274 查看基金资助信息 出版商 HINDAWI PUBLISHING CORP, 410 PARK AVENUE, 15TH FLOOR, #287 PMB, NEW YORK, NY 10022 USA 类别 / 分类 研究方向:Engineering; Mathematics Web of Science 类别:Engineering, Multidisciplinary; Mathematics, Interdisciplinary Applications 文献信息 文献类型:Article 语种:English 入藏号: WOS:000365524400001 ISSN: 1024-123X eISSN: 1563-5147 期刊信息 Impact Factor (影响因子): Journal Citation Reports® 其他信息 IDS 号: CX2KA Web of Science 核心合集中的 "引用的参考文献": 21 Web of Science 核心合集中的 "被引频次": 0 |
2楼2016-12-25 15:56:48
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3楼2016-12-25 15:57:00